The DOI matches its Crossref record; 5 of the 5 references it cites were found in a registry or an index.
Montreal Cognitive Assessment in Detecting Cognitive Impairment in Chinese Elderly Individuals: A Population-Based Study
Abstract
The Montreal Cognitive Assessment (MoCA) has been proved brief and sensitive to screen for mild cognitive impairment (MCI) and early dementia in some developed countries or areas. However, little MoCA data are available from mainland China. In this study, the MoCA was applied to 8411 Chinese community dwellers aged 65 or older (6283 = cognitively normal [CN], 1687 = MCI, and 441 = dementia). The MoCA norms were established considering significant influential factors. The optimal cutoff points were 13/14 for illiterate individuals, 19/20 for individuals with 1 to 6 years of education, and 24/25 for individuals with 7 or more years of education. With the optimal cutoffs, the sensitivity of the MoCA was 83.8% for all cognitive impairments, 80.5% for MCI and 96.9% for dementia, and the specificity for identifying CN was 82.5%. These indicate that with optimal cutoffs, the MoCA is valid to screen for cognitive impairment in elderly Chinese living in communities.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Folstein, M. F., Folstein, S. E., & McHugh, P. R. (1975) · Journal of Psychiatric Research · doi:10.1016/0022-3956(75)90026-6 · Cited by 88,282
The CES-D Scale: A Self-Report Depression Scale for Research in the General Population
Radloff, L. S. (1977) · Applied Psychological Measurement · doi:10.1177/014662167700100306 · Cited by 53,267
The Montreal Cognitive Assessment, MoCA: a brief screening tool for mild cognitive impairment
Nasreddine, Z. S., Phillips, N. A., Bédirian, V., Charbonneau, S., Whitehead, V., Collin, I., Cummings, J. L., & Chertkow, H. (2005) · Journal of the American Geriatrics Society · doi:10.1111/j.1532-5415.2005.53221.x · Cited by 25,553
The Mini‐Mental State Examination: A Comprehensive Review
Tombaugh, T. N., & McIntyre, N. J. (1992) · Journal of the American Geriatrics Society · doi:10.1111/j.1532-5415.1992.tb01992.x · Cited by 5,152
Statistics Notes: Diagnostic tests 2: predictive values
Altman, D. G., & Bland, J. M. (1994) · BMJ · doi:10.1136/bmj.309.6947.102 · Cited by 1,711
Cited by
Yang, L., Yan, Y., Wang, Y., Hu, X., Lu, J., Chan, P., Yan, T., & Han, Y. (2018) · Frontiers in Neuroscience · doi:10.3389/fnins.2018.00975 · Cited by 182
Self-citationZhao, W., Wang, X., Yin, C., He, M., Li, S., & Han, Y. (2019) · Frontiers in Neuroinformatics · doi:10.3389/fninf.2019.00013 · Cited by 145
Shu, N., Wang, X., Bi, Q., Zhao, T., & Han, Y. (2018) · Radiology · doi:10.1148/radiol.2017162696 · Cited by 135
Huang, L., Chen, K.-L., Lin, B.-Y., Tang, L., Zhao, Q.-H., Lv, Y.-R., & Guo, Q.-H. (2018) · Neuropsychiatric Disease and Treatment · doi:10.2147/ndt.s174293 · Cited by 112
Sun, Y., Dai, Z., Li, Y., Sheng, C., Li, H., Wang, X., Chen, X., He, Y., & Han, Y. (2016) · Radiology · doi:10.1148/radiol.2016151771 · Cited by 116
Metadata
- Authors
- Lu, J., Li, D., Li, F., Zhou, A., Wang, F., Zuo, X., Jia, X.-F., Song, H., & Jia, J.
- Venue
- Journal of Geriatric Psychiatry and Neurology
- Publisher
- SAGE Publications
- Published
- 2011-12
- Volume
- 24
- Issue
- 4
- Pages
- 184-190
- ISSN
- 0891-9887 (ISSN-L)
- 1552-5708
- OpenAlex
- W2035472651
- Cited by
- 581
- References
- 5
- FWCI
- 4.53
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Montreal Cognitive Assessment in Detecting Cognitive Impairment in Chinese Elderly Individuals: A Population-Based Study. https://app.cochat.ai/papers/10.1177/0891988711422528
- The paper
- Lu, J., Li, D., Li, F., Zhou, A., Wang, F., Zuo, X., Jia, X.-F., Song, H., & Jia, J. (2011). Montreal Cognitive Assessment in Detecting Cognitive Impairment in Chinese Elderly Individuals: A Population-Based Study. Journal of Geriatric Psychiatry and Neurology. https://doi.org/10.1177/0891988711422528
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
